NBjacobianRow: A jacobian function of the NB for the row scores

Description Usage Arguments Value

View source: R/F_NBjacobianRow.R

Description

A jacobian function of the NB for the row scores

Usage

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NBjacobianRow(
  beta,
  X,
  reg,
  thetas,
  muMarg,
  k,
  n,
  p,
  rowWeights,
  nLambda,
  rMatK,
  preFabMat,
  Jac,
  allowMissingness,
  naId
)

Arguments

beta

a vector of of length n + k +1 regression parameters to optimize

X

the data matrix of dimensions nxp

reg

a 1xp regressor matrix: outer product of column scores and psis

thetas

nxp matrix with the dispersion parameters (converted to matrix for numeric reasons)

muMarg

an nxp offset matrix

k

a scalar, the dimension of the RC solution

n

a scalar, the number of samples

p

a scalar, the number of taxa

rowWeights

a vector of length n, the weights used for the restrictions

nLambda

an integer, the number of lagrangian multipliers

rMatK

the lower dimension row scores

preFabMat

a prefab matrix, (1+X/thetas)

Jac

an empty Jacobian matrix

allowMissingness

A boolean, are missing values present

naId

The numeric index of the missing values in X

Value

a symmetric jacobian matrix of size n+k + 1


RCM documentation built on Nov. 8, 2020, 5:22 p.m.

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